Building ProcureAI: An AI-Powered Procurement Platform with Aurora PostgreSQL

JAGADEESH K — Sun, 28 Jun 2026 17:51:03 +0000

Inside the Build: How I Leveraged v0 and AWS to Ship a Production-Grade B2B SaaS

Welcome, builders, tech enthusiasts, and curious minds.
We’ve all seen hackathon projects that look like a million bucks on the surface but are held together by digital duct tape and wishful thinking underneath. When I entered my latest hackathon, I didn't want to build a "random vibe code" project. I wanted to build something that could survive the real world—a full-fledged, production-grade B2B web application.
To pull this off under a tight hackathon deadline, I paired the lightning-fast generative UI capabilities of v0 with the robust enterprise infrastructure of AWS.
Grab a coffee. We are diving deep into the development sea.

The Blueprint: From a Single Block to a Castle

Every great architectural marvel starts with a single block. For this product, that block was a disciplined, four-tier engineering framework:
By adhering strictly to this pipeline, I avoided the classic developer trap: writing code before understanding the problem.

Phase 1: The Groundwork (The Research)

Before you write a single line of a Dockerfile or prompt a component into existence, you have to understand the business logic. If you don't understand the ecosystem, you're just building a beautiful solution for a problem that doesn't exist.
I chose to tackle Procurement Management in the B2B sector—a domain notorious for friction, legacy software bottlenecks, and fragmented workflows. To validate the problem statement, I didn't just guess; I stress-tested the idea using an AI-driven research stack:

ChatGPT & Gemini: Utilized for rapid brainstorming and simulating user personas (Procurement Officers, Vendors, CFOs).
Perplexity: Used to gather real-time data on modern B2B supply chain bottlenecks and compliance standards. > The Golden Rule of B2B SaaS: Know your roles, know your flows, and know your breaking points. > Before touching v0, I mapped out the entire user journey. I identified exactly who interacts with the system, what regulatory compliance checkpoints were required, and where the data pipelines could fail. I translated this mental model into a clean, simple architecture flow diagram. It wasn’t a masterpiece meant for a design portfolio; it was a functional blueprint meant for execution. With the roadmap locked in, the research phase was complete. Next stop? Building the actual MVP.

Phase 2: Building the MVP (The Foundation)

Every nook and corner matters when building a product. You can't just type a generic prompt and expect v0 to spit out a flawless, production-ready system. Total ambiguity yields total chaos. Asking an AI to "create an enterprise-grade app" won't work; you need to dictate the specific stack, data flow, and architecture (for example, explicitly choosing Next.js with the App Router over the Pages Router).

Formulating the AI Strategy

When working with v0, you must choose the mode that matches your task size. Don't make a "senior dev" LLM (like a max token agent) center a div. Use mini models for quick, minimal tasks, and save the heavy-hitting models for complex structural layouts.
Once the foundation is stable, it's time to build the "rooms" of your application. Think of it like a restaurant: a chef should only work in the kitchen. In a B2B SaaS app, this means establishing strict role-based access control (RBAC).
Our procurement platform required five distinct user views:
Roles and their Permitted Actions & Views
Admin - Full system configuration, user management, and global logs. Procurement Manager-Creates requests, initiates RFQs, and manages vendor pipelines.
Approver / Finance - Reviews budget allocations, signs off on high-value quotes.
Auditor - Read-only access to historical logs, compliance metrics, and invoice matching.
Vendor - Views open RFQs, submits pricing bids, and uploads final invoices.
By mapping these out early, I analyzed overlapping UI layouts to maximize component reusability. Once the interface was locked down, I stitched together the functional core business logic:
With this core loop fully operational, the MVP was officially alive.

Phase 3: Enhancing, Polishing, and Hardening

An MVP gets you into the game, but optimization keeps you there. Phase 3 was entirely about code cleanup, security hardening, and database optimization.

Database Architecture: Why Aurora PostgreSQL?

Because procurement is inherently relational—requiring heavy JOIN operations, audit trails, and complex WHERE filters across complex schemas—Amazon Aurora PostgreSQL was the obvious choice.
To prevent connection exhaustion during high-concurrency spikes, I integrated an AWS RDS Proxy between the application and the database cluster. This pooled connections efficiently and kept the app highly responsive.
Our architecture will actually be :
[Next.js App] ──> [Clerk Auth Component]──>[Drizzle ORM] ──> [AWS RDS Proxy] ──> [Amazon Aurora DB Cluster]

Security Checkpoints

Before moving a single step closer to deployment, I initiated a manual security audit:

Log Sanitization: Scrubbed the codebase to remove console.log statements that could accidentally expose sensitive enterprise data or internal object structures.
Authentication & Session Testing: Attempted to bypass the login pages, manually test URL endpoints without an active session token, and verified that a user could not access authenticated views post-logout. ## Phase 4: Production and Final Deployment Moving from development to production means moving from a controlled sandbox to the wild west of real-world usage. One of the biggest hurdles during this phase was configuring Clerk for authentication. There are a few critical architectural choices you have to make right out of the gate:
Component vs. Function: Deciding whether to drop in Clerk's pre-built UI components or build a custom flow using their SDK functions.
Multi-Tenancy: Deciding if your database needs native organization management. For a B2B procurement platform, multi-tenancy was non-negotiable. Configuring Clerk’s Organizations feature allowed us to partition data safely so Corporation A could never catch a glimpse of Corporation B's data supply lines. Once the production environment was configured on AWS and the environment variables matched our isolated production database, we hit deploy.

The Takeaway

Building a functional B2B app during a hackathon isn't about writing code faster; it's about shifting your development paradigm. By leveraging v0 to handle the heavy lifting of UI prototyping and scaffolding, I freed up critical mental bandwidth to focus on what truly matters: robust business logic, role security, and a bulletproof AWS data infrastructure.
Stop writing "vibe code." Plan your flows, pick your tools intentionally, and build things that last. Happy hacking!

DEV Community: JAGADEESH K